Hybrid tool + evidence report
AGV in Warehouses Feasibility Tool
Screen warehouse AGV fit from loaded moves, shifts, payload, and environment. Then use the report to check ROI boundaries, floor readiness, traffic risk, safety requirements, and RFQ inputs.
Key Decision Conclusions
The calculator gives the fast answer first. These report conclusions explain when the result should advance to simulation, supplier quotation, and safety review.
Use the tool as a screening gate
The calculator estimates fleet count from peak loaded moves, shifts, payload, and environment. It is designed to decide whether a formal simulation and quote are worth preparing, not to replace supplier engineering.
Evidence: The page exposes the sizing formula, payback boundaries, and excluded costs beside the result.
Repeatable pallet routes are the strongest fit
AGVs work best when routes, pickup points, and drop-off points are stable. Dynamic pick faces, frequent manual forklift crossings, and temporary aisle blockage usually reduce real throughput.
Evidence: MHI readiness guidance stresses repeatable flows, process maturity, and clean warehouse data before automation.
Safety and floor checks are launch gates
A project should not move from screening to RFQ until traffic separation, stopping distance, load class, floor condition, and pedestrian interaction are documented.
Evidence: ISO 3691-4:2023 covers driverless industrial truck safety; OSHA warehousing guidance frames the pedestrian and powered-truck hazard context.
Calculator Method and Limits
The model is deliberately conservative: it shows assumptions, limits, and excluded costs so the output can be challenged before a purchasing decision.
| Model Input | Assumption | Decision Limit |
|---|---|---|
| Fleet sizing | 1 AGV handles 15 loaded moves per vehicle-hour, then the page applies a 20% peak buffer. | Actual rates depend on route length, dwell time, doors, lifts, charging strategy, and traffic rules. |
| Payback band | Shift count changes the screening band: one shift is harder to justify, while 24/7 routes normally clear payback faster. | The band excludes floor repair, chargers, fleet software, WMS work, validation, and production disruption. |
| Payload | 100-2000 kg is treated as a standard pallet/cart range; heavier loads lower fit confidence. | Heavy loads can change chassis, wheel, brake, and floor requirements enough to require custom engineering. |
| Environment | Standard ambient warehouses receive the highest fit score; cold storage and dynamic layouts add risk warnings. | Battery behavior, condensation, tire traction, and layout churn must be validated before quote comparison. |
Warehouse Pattern Fit
AGV success depends less on the vehicle catalog and more on route discipline, handoff design, and whether exceptions can be managed without manual workarounds.
| Warehouse Pattern | Fit | Why It Scores This Way | Next Evidence to Collect |
|---|---|---|---|
| Dock-to-storage pallet transfer | High | Stable origin/destination pairs, repeatable lanes, and clear handoff points. | Collect peak-hour moves, route distance, pallet weights, and staging dwell times. |
| Production line replenishment | High | Scheduled milk-run or tugger loops are usually route-repeatable and easy to simulate. | Map takt time, empty-container return flow, and line-side space constraints. |
| Cold storage movement | Medium | The route may be repeatable, but battery, traction, condensation, and door cycles add risk. | Ask suppliers for battery derating, tire material, and condensation controls. |
| Mixed forklift and pedestrian aisles | Medium | Frequent stops can erase the calculated throughput advantage. | Separate traffic or model speed zones and controlled crossings before RFQ. |
| Frequently reconfigured pick zones | Low | Route stability is weak; AMRs or manual processes may adapt faster. | Compare AGV, AMR, and hybrid concepts before specifying fixed-route vehicles. |
Implementation Risks and Mitigations
| Risk Factor | Trigger | Impact | Mitigation |
|---|---|---|---|
Ignoring floor quality | Deploying AGVs on uneven, cracked, or high-friction floors without a pre-deployment survey. | Navigation errors, braking variation, sensor tilt, wheel wear, and avoidable maintenance calls. | Survey the route, document tolerances against supplier requirements, and price repair before RFQ. |
Underestimating peak throughput | Sizing the fleet from average daily volume instead of the busiest sustained hour. | Bottlenecks during receiving, shipping, or shift-change peaks can force manual overflow. | Model peak moves with a buffer, include dwell time, and confirm traffic behavior in simulation. |
Mixed traffic interference | Running AGVs in aisles shared by manual forklifts, pedestrians, and ad hoc staging. | Safety stops and blocked routes reduce delivered moves per hour below the business case. | Define lanes, crossings, speed zones, right-of-way rules, and fleet-control requirements. |
Thin WMS and PLC integration scope | Treating AGVs as standalone vehicles instead of a warehouse execution workflow. | Manual dispatch, duplicate scans, and unclear exception handling reduce adoption. | Document task release logic, handshake points, exception states, and interface ownership. |
RFQ Readiness Checklist
A calculator pass is not enough for procurement. Package these items before asking vendors to size vehicles, drive wheels, fleet software, and charging systems.
Request RFQ packet reviewRoute drawing with origin, destination, crossings, doors, and staging buffers.
Peak loaded moves per hour, shift schedule, dwell time, and empty-return logic.
Payload range, load stability, cart or pallet interface, and lift requirements.
Floor survey, aisle width, pedestrian zones, and current forklift traffic rules.
WMS, PLC, scanner, and fleet-control interface ownership.
Exception plan for blocked routes, manual override, charging, and maintenance.
Evidence and Source Limits
Time-sensitive source checks are marked with exact dates. ROI claims are kept as planning bands because final economics depend on site layout, safety validation, integration scope, and supplier pricing.
| Source | How It Is Used | Checked |
|---|---|---|
| ISO 3691-4:2023 | Safety baseline for driverless industrial trucks, including personnel detection, speed, stopping, and operating-zone requirements. | 2026-07-29 |
| OSHA Warehousing guidance | Hazard context for warehouse traffic, powered industrial trucks, pedestrians, storage, and loading dock operations. | 2026-07-29 |
| MHI automation readiness guidance | Process-readiness framing for when warehouse automation is suitable: clean data, repeatable workflows, and operational maturity. | 2026-07-29 |
| VDA 5050 interface initiative | Procurement reference when multiple AGV/AMR systems, fleet managers, or interface ownership questions are in scope. | 2026-07-29 |
| AGV Drive Wheel screening model | Page-specific calculator assumptions: 15 loaded moves per vehicle-hour, 20% peak buffer, payload ranges, and payback bands. | 2026-07-29 |
Decision paths
Related Warehouse AGV Planning Guides
Use these route, navigation, and handling guides when the calculator points to a supplier-ready or borderline warehouse AGV case.
Warehouse AGV route-fit guide
Compare warehouse AGV lanes, payloads, and route constraints.
Warehouse AGV automation planning
Map automation scope before supplier layout review.
AGV tugger routes
Check tugger trains for line-feed and replenishment loops.
AGV forklift comparison
Compare pallet handling options before selecting vehicle type.
Material handling robots
Place AGVs beside AMRs, conveyors, forklifts, and hybrid systems.
AGV navigation methods
Match magnetic, laser, QR, natural, and hybrid navigation.
Ready for supplier-level sizing?
Use the calculator output and checklist as the first RFQ packet. The next useful artifact is a route simulation with peak-hour moves, safety zones, and charging assumptions.